Field of the Invention
The present invention relates to a method for active acoustic control of narrow-band disturbing noise(s) implementing a model of an electroacoustic system of a space in which the disturbing noise to be attenuated/cancelled is present. This electroacoustic system corresponds to a space including one/several loudspeaker(s) for generating counter-noises and one/several error microphone(s) for acoustic measurements in said space. The invention is particularly adapted to the case where the electroacoustic system varies over time. The variation of the electroacoustic system, and hence of the model that represents it, may be due, for example, to a displacement in the space of the source(s) of disturbing noises and of the error microphone(s) or to a change in the configuration of this space and/or in the position of the objects it contains. In practice, the method may implement one/several transfer function(s), a transfer matrix, or a state representation of the model of the electroacoustic system. The object of this method is to obtain at least attenuation, or even cancelling, of the disturbing noises, in particular in a zone of the space in relation with the error microphone(s).
Description of the Related Art
The transfer between the counter-noise loudspeaker(s) and the error microphones in the electroacoustic system is generally called “secondary path transfer” and this denomination will be used hereinafter.
The variations of the secondary path transfer may be due to several factors, in particular:                a variation of configuration of the space around the counter-noise loudspeakers and the error microphones, according to the arrangement of the objects and/or the people located in this space;        a modification of the loudspeaker(s) or the microphone(s) due for example to an ageing of these elements;        a modification of position of the loudspeaker(s) or the microphone(s), and, in this latter case, due to the fact that the microphone(s) are placed on a person who moves in space and who wishes to be protected to from the disturbing noise.        
It is known that two main classes of active control algorithms exist:
1) The “feedforward” algorithms, which require the use of a reference source correlated with the disturbing noise perceived at the error microphone(s). This reference measurement serves to feed a filter whose output is the control signal of the counter-noise loudspeaker(s). The coefficients of the filters being adjusted in real time/in line by means of an adaptive device. The algorithms of the LMS series (Fx-LMS, etc.) belong to this class.
2) The “feedback” algorithms, in which only the measurements of the error microphones are used as an input for the algorithm, independently of any reference.
The problem that this invention proposes to solve relates to the rejection of narrow-band disturbing noises by means of a feedback algorithm and when the secondary path transfer varies over time, in particular for the above-mentioned reasons.
During the feedback synthesis of a linear corrector, the margin of robustness of the corrector control law is known from the design. In the single-variable case, this level of robustness may be evaluated in particular by means of the gain, phase, module, delay margins, etc.
In the case of a narrow-band noise rejection, a conventional linear control law with invariant parameters (LTI) produces naturally a phase margin Mφ that cannot exceed 90° in absolute value and whatever the methodology of synthesis of said control law. As a consequence, if the phase of secondary path transfer comes to vary more than Mφ, the loop becomes instable and a Larsen effect is obtained.
In a lot of cases, the natural robustness of a LTI control law is insufficient when the secondary path transfer varies significantly, which strongly limits the applications of the active control in the practice, when it is compelled to use only electroacoustic systems of the LTI or quasi-LTI type.
To that, it must be added that the variations of the secondary path transfer are all the more important that the frequencies of interest, which correspond to the frequencies of rejection, are high, which is one of the reasons for which the active acoustic control is used generally only for the low frequencies.
In order to solve the problem of active control of electroacoustic systems whose secondary path transfer varies significantly over time, two automation approaches exist in the literature:
1) The Adaptive Control:
The adaptive control is, as its name indicates, a control law where the corrector coefficients are adapted over time as a function of the variation of the coefficients of the transfer function or of the transfer matrix, of the system to be controlled.
Two sub-categories of adaptive control exist, as mentioned in the document Landau et al., “Adaptive control”, Springer, 2011:
a) The direct adaptive control where the coefficients of the controller are calculated so that the closed loop tends, as far as the dynamics is concerned, to be similar to the dynamics of a reference model. Unfortunately, this method requires that all the zeros of the transfer function are in the unit circle, which has little chance to occur in practice for an electroacoustic system. The scheme of principle of the direct adaptive control is given in FIG. 1 of the state of the art.
The signals indicated in this FIG. 1 and in the remaining of this document are the following (in the case of a time representation):                U(k) is the control signal, or the vector of control signals, of the counter-noise loudspeakers;        Y(k) is the signal, or the vector of signals, of the measurements of the error microphones;        P(k) is the signal equivalent to the disturbing noise to be rejected at the error microphone(s).        
b) The indirect adaptive control, which is consisted of two stages:                a stage of identification of model in line, real time, of the system parameters producing the coefficients of the model identified;        a stage of calculation in line, real time, of the corrector parameters based on the model identified in real time by its model coefficients.        
The scheme of principle of the indirect adaptive control is given in FIG. 2 of the state of the art.
This indirect adaptive control scheme is in theory usable within the framework of the narrow-band active control. Unfortunately, the obstacles linked to the implementation of this principle are essentially of practical order. Indeed, an electroacoustic system is by nature a system with distributed parameters, i.e. whose number of state variables is theoretically infinite. When these systems are modelled by means of finite-dimension models, in particular by transfer function(s), state representation . . . , the number of variable coefficients or states of the model is necessarily high and the corresponding transfer functions are hence of high order. For example, for a single-variable system, it is not rare to have models of order 15 or 20, i.e. 30 or 40 variables. For a multi-variable system, the number of variables may easily exceed one hundred. In the context of the adaptive control, this implies that this hundred, or more, of variable is identified in real time/in line, which, taking into account the sampling frequencies generally used, several thousands of Hz, leads to a volume of calculation that is fully redhibitory for a calculation in real time and an acceptable cost.
The difficulties linked to the volume of calculation are further increased when considering that the corrector parameters must also be calculated from the parameters of the identified model of the electroacoustic system corresponding to the secondary path transfer. This step induces significant intermediate calculations as, for example, solving a Bézout equation for a RST corrector by pole placing or solving a Riccati matrix equation in the case of quadratic-optimization control laws, etc. In practice, these calculations are performed offline with CAD tools (Matlab, Scilab . . . ) which cannot be integrated in real time systems. The size of the model and hence of the corrector makes these corrector synthesis calculations still harder to perform in real time.
Hence, the implementation in real time of an adaptive control such as described in the literature is almost not possible in practice.
2) The Multi-Model Control:
In this principle of control, n models Mi are identified for the various configurations of the system. For example, if the error microphones are mobile, different model identifications are performed in various possible locations for said microphones.
For each model, a corrector is synthesized and the control law is based on the selection, in real time/in line, of the good corrector according to the present/current configuration of the electroacoustic system, and in particular, of the location of the loudspeakers, of the microphones, of the arrangement of the zone to be controlled, etc. On the other hand, the identification of the models and the synthesis of the correctors may be performed beforehand, not in real time.
In the case of mobile microphones, the choice in real time of the good corrector may be made by determining the current position of the error microphone(s) in the space, with an external detection system, and the model and the corrector chosen are those which have been previously obtained at a point that is the closest to the current position.
It is also possible to estimate in real time the “proximity” of the behaviour of each of the models Mi previously identified with the current behaviour of the electroacoustic system and to choose the corrector based on the model that is the closest to the current electroacoustic system, at a given instant. This requires the injection of an additive noise into the control loop. These techniques have been described in the patent application FR12/62353, whose inventor is B. VAU and which has been filed by the IXBLUE company. A description of the general principle of the multi-model control may also be found in the document Landau et al., “Adaptive control”, Springer, 2011.
One of the drawbacks of this latter approach lies in that the number of models may very easily become too high if the configurations of the electroacoustic system are numerous. For example, in the case of mobile microphones as described in the patent application FR12/62353, it is compelled to perform a meshing of points in the space, wherein, at each point of the meshing, a model is identified and the corrector corresponding to the model is synthesized, which may be performed beforehand, not in real time.
On the other hand, in case of application in real time of the models and correctors obtained, if their number increases too much, the volumes of data and of calculation may here also become prohibitive for a processing in real time, and in particular, in applications requiring an on-board calculator, for example in a vehicle.